Dataset on substituents effect on biological activities of linear RGD-containing peptides as potential anti-angiotensin converting enzyme

The angiotensin converting enzyme inhibiting activity of linear rgd-containing peptides was investigated using in silico approach. The synthesized compound (parent compound) using experimental approach as well as its derivatives was subjected to computational examination using appropriate software. The investigated compounds were optimized using Spartan 14 while the docking study was executed via Pymol, AutoDock Tool, AutoDock Vina and discovery studio. The descriptors obtained (2D and 3D) were screened and the descriptor with highest capacity (squared correlation coefficient) was correlated to the calculated binding affinity. More so, the docking analysis was performed on the investigated linear rgd-containing peptides and angiotensin converting enzyme (PDB ID: 3nxq) via docking software and the resulted scoring and the types of the interaction observed were presented. Furthermore, (S)-dimethyl 2-(2-((S)-2-((R)-1-((S)-2-((S)-2-((S)-3-(4-chlorophenyl)-2-(1,3-dioxoisoindolin-2-yl)propanamido)-4-(methylthio)butanamido)-4-methylpentanoyl)pyrrolidine-2-carboxamido)-5-(3-((2,2,4,5,7-pentamethyl-2,3-dihydrobenzofuran-6-yl)sulfonyl)guanidino)pentanamido)acetamido)succinate (AB5) (compound with lowest binding affinity) and metformin were subjected to ADMET analysis and the resulted outcome were reported appropriately.


Value of the Data
• The chemical shift obtained from the HNMR will enable the scientists to understand the position and number of the Hydrogen atoms present in the peptide. • It helps researchers in ascertaining and elucidating the right structure of the peptide.
• The generated data from the 3D structure of the linear RGD-containing peptides will expose scientists to their anti-angiotensin converting enzyme activities. • The calculated 2-dimensional and 3-dimensional descriptors from the optimized compounds will give scientists better understanding about appropriate features that describes antiangiotensin converting enzyme activities of linear RGD-containing peptides. • The calculated binding affinity from the docked complexes will reveal to researchers compounds with superior tendency to inhibit angiotensin converting enzyme (PDB ID: 3nxq). • The level of absorption and its ability to act as drug via ADMET analysis will help scientists to know the probable action of individual molecule (drug-like molecules) in human being.

Objective
To investigate the anti-angiotensin converting enzyme activity of the linear rgd-containing peptides via quantum chemical and molecular modelling investigations using in silico approach. Table 1 showed the combination of three dimensional structures (optimized using Spartan 14 software [ 1 , 2 ]), two-dimensional structure and the IUPAC names of the investigated compounds.

Experimental Design, Materials and Methods
The peptide was synthesized from solid phase peptide synthesis using 2-Chlorotrityl chloride resin. The coupling of the Fmoc-protected amino acids were achieved with Oxyma, NMP and DIC as coupling agent, 20% of piperidine in DMF was used for the deprotection of Fmoc and the peptide was cleaved from resin via 2% trifluoracetic acid in DCM. The crude peptide was esterified with thionyl chloride in methanol to obtain the final product [5][6][7] .
Moreover, the parent compound together with its six derivatives was subjected to optimization using Spartan 14 tool [ 1 , 2 ]. The calculation was set up on core i5, 250GB SSD, 8GB ram and 64-bit operating system, x64-based processor system. The speed for each of the calculation for individual compound was observed to be a function of the size of the compound, the capacity of the system used for the calculation as well as the basis set used. In this work, semi-empirical method was employed and PM3 was used as basis set in the optimization of the investigated compounds. The completion of individual compound brought about series of descriptors with different values except band gap which requires manual calculation (E LUMO -E HOMO ). The calculated descriptors were located in the properties of the optimized ligand which were retrieved and reported. The ligand (linear rgd-containing peptides) was converted to .pdb format after optimization and further subjected to .pdbqt using AutoDock tool software [8] . The appropriate receptor (angiotensin converting enzyme (PDB ID: 3nxq) [3] ) was retrieved from online protein database (protein data bank) and cleaned by removing other materials (water molecules, small ligands etc.) downloaded with the receptor using discovery studio software [9] . The binding site in the downloaded protein (Receptor) was identified using AutoDock Tool [8] and the calculated value obtained for X,Y and Z direction were 3.419222 (center_x), -14.815222 (center_y) and -18.028222 (center_z) while 40, 40 and 40 were used for size_x, size_y and size_z respectively ( Fig. 11 ). The exhaustiveness was set to be 8. The main docking calculation was performed via AutoDock Vina [10] . More so, the correlation between the descriptors and the calculated binding affinities were executed using Microsoft Excel and the correlation with R 2 ≥ 0.5 was reported. Compound AB5 (compound with greatest binding affinity) and Metformin were screened for absorption, distribution, metabolism, excretion and toxicity analysis.

Ethics Statement
This study does not involve studies with animals and humans.

Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships which have or could be perceived to have influenced the work reported in this article.